In this proposal, we will develop a platform for the high-throughput measurement of growth and gene expression in single bacterial cells. Time-lapse microscopy of growing bacteria has been an extremely successful technique, revealing the natural heterogeneity that underlies growth and gene expression in single cells. However, the exponential growth of bacteria quickly overwhelms the solid support, depleting the local nutrient environment, crowding cells, and limiting measurement duration. Here, we will circumvent the low throughput of such measurements by combining microfluidic techniques, microarray technology, and automated image analysis to create a massively parallel, high-throughput, single-cell 'chip'-a living analog of the DNA microarray. In our first aim, we will continue our construction of a single-cell chemostat-a micro-patterned pad that can be used to cultivate a high density of cells for long durations while allowing individual cells to be imaged. We use soft-lithography to create nano-patterned hydrogel pads that constrain bacteria to high-density linear tracks. Buffer flow through microfluidic lines in the gel delivers fresh nutrient bufer and washes away excess cells. Soft and porous hydrogels hold cells in place with a non-perturbative pressure and allow unrestricted diffusion to maintain a uniform nutrient environment. We will focus on creating a device that allows real-time control over the nutrient environment and precise control over the mechanical properties of the hydrogel that holds the cells. This single-cell chemostat will dramatically increase both the duration of time-lapse measurements and the number of cells that can be imaged in a field-of-view. In our second aim, we will develop methods to leverage existing microarray technology to print thousands of distinct bacterial strains onto a single patterned hydrogel. We will pursue two approaches for printing cells to patterned pads, both of which have been validated by proof-of-principle experiments. Advances in this aim will allow multiple experiments to be run in parallel on a single patterned hydrogel, providing a dramatic increase in the number of distinct bacterial strains that can be characterized simultaneously. In our final aim, we will develop the necessary image-based techniques to perform high-speed, high- throughput, time-lapse microscopy of growth on a nano-patterned pad, and we will develop the automated image analysis software needed to extract the full history of growth, division, and fluorescent gene expression within cellular lineages from these large data sets. These techniques will allow us to monitor the entire life of millions of cells in a single overnight measurement. These advances will make high-throughput, single-cell studies possible in our laboratory. We will be able to characterize the transcriptional network that regulates the assembly of complex, multi-protein machines such as the flagella; and investigate the transcriptional response to multiple antibiotic stresses-a proble that is extremely relevant to human health. Moreover, by providing a platform for high-throughput single-cell measurements, our cellular chip will prove a useful tool for answering many pressing questions in microbiology.